Fetal health classification: a deep learning model with enhanced interpretability and lightweight deployment

Med Biol Eng Comput. 2026 Apr 6. doi: 10.1007/s11517-026-03525-z. Online ahead of print.

¹ Department of Science and Engineering, Southampton Solent University, Southampton, SO14 0YN, UK. raza.hasan@solent.ac.uk.
² Department of Computer Science and Management Information System, College of Management & Technology, P.O. Box 680, Barka, 320, Oman.
³ Department of Computer Science, Nazeer Hussain University, ST-2, Near Karimabad, Karachi, 75950, Sindh, Pakistan.
⁴ Department of Computing and Electronics Engineering, Middle East College, Muscat, Oman.
⁵ School of Technology and Maritime Industries, Southampton Solent University, E Park Terrace, Southampton, Hampshire, SO14 0YN, UK.
⁶ Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, NE1 8QH, UK.

No abstract available

Keywords: Deep learning; Feedforward neural network (FNN); Fetal health classification; Machine learning; Model interpretability.